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A Charge/Discharge Plan for Electric Vehicles in an Intelligent Parking Lot Considering Destructive Random Decisions, and V2G and V2V Energy Transfer Modes

Author

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  • Mahyar Alinejad

    (School of Electrical Engineering, Iran University of Science and Technology, Tehran 13114-16846, Iran)

  • Omid Rezaei

    (School of Electrical Engineering, Iran University of Science and Technology, Tehran 13114-16846, Iran)

  • Reza Habibifar

    (School of Electrical Engineering, Sharif University of Technology (SUT), Tehran 14588-89694, Iran)

  • Mahdi Azimian

    (Department of Electrical and Computer Engineering, Kashan Branch, Islamic Azad University, Kashan 87159-98151, Iran)

Abstract

The random decisions of electric vehicle (EV) drivers, together with the vehicle-to-vehicle (V2V) and vehicle-to-grid (V2G) energy transfer modes, make scheduling for an intelligent parking lot (IPL) more complex; thus, they have not been considered simultaneously during IPL planning in other studies. To fill this gap, this paper presents a complete optimal schedule for an IPL in which all the above-mentioned items are considered simultaneously. Additionally, using a complete objective function—including charging/discharging rates and prices, together with penalties, discounts, and reward sets—increases the profits of IPL and EV owners. In addition, during peak times, the demand for energy from the distribution system is decreased. The performance of the proposed schedule is validated by comparing three different scenarios during numerical simulations. The results confirm that the proposed algorithm can improve the IPL’s benefits up to USD 1000 and USD 2500 compared to the cases that do not consider the V2V and V2G energy transfer modes, respectively.

Suggested Citation

  • Mahyar Alinejad & Omid Rezaei & Reza Habibifar & Mahdi Azimian, 2022. "A Charge/Discharge Plan for Electric Vehicles in an Intelligent Parking Lot Considering Destructive Random Decisions, and V2G and V2V Energy Transfer Modes," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12816-:d:936004
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    References listed on IDEAS

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    1. Rahbari, Omid & Vafaeipour, Majid & Omar, Noshin & Rosen, Marc A. & Hegazy, Omar & Timmermans, Jean-Marc & Heibati, Seyedmohammadreza & Bossche, Peter Van Den, 2017. "An optimal versatile control approach for plug-in electric vehicles to integrate renewable energy sources and smart grids," Energy, Elsevier, vol. 134(C), pages 1053-1067.
    2. Drude, Lukas & Pereira Junior, Luiz Carlos & Rüther, Ricardo, 2014. "Photovoltaics (PV) and electric vehicle-to-grid (V2G) strategies for peak demand reduction in urban regions in Brazil in a smart grid environment," Renewable Energy, Elsevier, vol. 68(C), pages 443-451.
    3. Omid Rezaei & Reza Habibifar & Zhanle Wang, 2022. "A Robust Kalman Filter-Based Approach for SoC Estimation of Lithium-Ion Batteries in Smart Homes," Energies, MDPI, vol. 15(10), pages 1-21, May.
    4. Yongyi Huang & Atsushi Yona & Hiroshi Takahashi & Ashraf Mohamed Hemeida & Paras Mandal & Alexey Mikhaylov & Tomonobu Senjyu & Mohammed Elsayed Lotfy, 2021. "Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation," Sustainability, MDPI, vol. 13(11), pages 1-14, May.
    5. Jin Li & Feng Wang & Yu He, 2020. "Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
    6. Qiongjie Dai & Jicheng Liu & Qiushuang Wei, 2019. "Optimal Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Station Design Based on Multi-Agent Particle Swarm Optimization Algorithm," Sustainability, MDPI, vol. 11(7), pages 1-21, April.
    7. Jannati, Jamil & Nazarpour, Daryoush, 2018. "Multi-objective scheduling of electric vehicles intelligent parking lot in the presence of hydrogen storage system under peak load management," Energy, Elsevier, vol. 163(C), pages 338-350.
    8. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    9. Goodarzi, Mostafa & Li, Qifeng, 2022. "Evaluate the capacity of electricity-driven water facilities in small communities as virtual energy storage," Applied Energy, Elsevier, vol. 309(C).
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    2. Monir Sadat AlDavood & Abolfazl Mehbodniya & Julian L. Webber & Mohammad Ensaf & Mahdi Azimian, 2022. "Robust Optimization-Based Optimal Operation of Islanded Microgrid Considering Demand Response," Sustainability, MDPI, vol. 14(21), pages 1-17, October.

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